Published on 12 August 2026
Peter Challenor – University of Exeter
Yueyue Chai – University of Exeter
Elizabeth Galloway – University of Exeter
Pippa Langford – Natural England
Carina Humberstone – Natural England
Em Pope – Natural England
Protecting and restoring natural spaces is critical in the face of climate risks and environmental change, whilst at the same time, access to natural space plays an important role in population health and well-being. Understanding patterns of visits to natural spaces aids planning, maintenance, and land use, and allows us to evaluate the impact of interventions designed to benefit both nature and society. While surveys (e.g. Natural England’s People and Nature Survey) can provide snapshots of information about visits to natural spaces and visitor’s socio-economic characteristics, robustly measuring visitor patterns and profiles on broad scales remains a challenge. Moreover, we lack the tools required to provide estimates of visitor numbers under the range of scenarios involved in land use and natural space planning.
Researchers in RENEW’s Environmental Intelligence team are collaborating with Natural England and Defra on their Recreation & Engagement Activity Monitoring (REAM) project, building on previous work by the Office for National Statistics (ONS). Our research is using advanced statistical modelling and machine learning methods to develop scalable tools to predict visitor counts along paths in England and Wales located in natural spaces. This project aims to:
Using anonymised data from the running, cycling, and hiking app Strava (via Strava Metro), and experimenting with other mobile phone positional data, we have built models of varying complexity that predict how many people visit green and blue spaces. The models draw on additional data (meteorology, census, points-of-interest, environmental and ecological data) to account for a range of factors that influence people’s use of outdoor spaces, e.g. the weather, demography (not everyone is as active as Strava users), local points of interest and environmental/landscape features, and the number of dog walkers (because people with dogs do much more walking). The models are calibrated against data from automated people counters deployed at various sites in England and Wales, which measure the number of people who walk past a certain point over time. We have we tested our modelling by comparing it to the number of visitors actually counted at sites not included in the models.
On the whole, the modelled predictions perform well, but there are still some sites where the models predict badly. We are working on understanding why this is and how we can improve the models further. Alongside improving predictive capabilities, we are working to identify key factors that are critical to visitor numbers and investigate how their impacts vary with changes in visitor numbers. We are also developing ways to extend our methods from estimating the number of visitors passing a single point in space to estimating the number along a footpath or in areas such as a nature reserve.
In addition, we are carrying out a user needs assessment to better understand how our models could be used in practice. We have devised a survey for staff and volunteers working for organisations in England who manage protected sites and/or recreational green and blue spaces. We are interested in understanding if and how the models could be adopted for use in planning, decision making, or research relating to the management of natural spaces used for recreational purposes. We hope to reach a broad spectrum of stakeholders across government and arm’s length bodies, environmental NGOs, protected landscapes, and academia working on conservation and access. Whilst the survey is primarily targeting organisations in England, we hope it will reach and be relevant to organisations across the UK.
Our models demonstrate promising ability to predict visitor patterns at many sites, suggesting data-driven methods could offer valuable insights into the sustainable management of natural spaces. We are in the process of producing a project report and several academic papers, which will detail our methods, analysis, and recommendations. We are also developing an accessible front-end dashboard which will allow practitioners to use and benefit from the models. We hope that this work will be valuable for anyone seeking to balance the conservation of green and blue spaces with managing visitor access.
Outputs will be linked here when published.
Photo by Vitaly Gariev on Unsplash
